WebFeb 18, 2024 · Batch Steganography via Generative Network Abstract: Batch steganography is a technique that hides information into multiple covers. To achieve a better performance on the security of data hiding, we propose a novel strategy of batch steganography using a generative network. WebNov 1, 2024 · Compared with the recent image steganography based on generative adversative network, HCGAN provides more accurate supervised information, which makes the training process of HCGAN converge faster and the performance of the trained image steganography network is better. In addition, this article introduces an image …
Perfectly Secure Steganography Using Minimum Entropy Coupling
WebMar 16, 2024 · A generative adversarial network (GAN), an effective deep learning framework, is used to encode secret messages into the cover image and optimize the … WebDec 13, 2024 · A novel strategy of Secure Steganograpy based on Generative Adversarial Networks is proposed to generate suitable and secure covers for steganography with significant improvements made on the convergence speed, the training stability and the image quality. 144 PDF Generating steganographic images via adversarial training … 2 10 14魔塔
Provably Secure Generative Linguistic Steganography
WebAug 8, 2024 · Design a network structure of binary image steganography technology based on a generative adversarial network. The proposed method is the first to apply the GAN network to binary image steganography. Previous GAN networks cannot be used for binary image steganography. 2. Design a new embedded simulator for binary image … WebJul 28, 2024 · An advanced generative steganography network (GSN) that can generate realistic stego images without using cover images and a novel hierarchical gradient decay (HGD) skill is developed to resist … WebJul 17, 2024 · With the development of Generative Adversarial Networks (GAN), GAN-based steganography and steganalysis techniques have attracted much attention from researchers. In this paper, we propose a novel image steganography method without modification based on Wasserstein GAN Gradient Penalty (WGAN-GP). 2 16乗